dnnl::convolution_forward::desc Struct Reference

Descriptor for a convolution forward propagation primitive. More...

#include <dnnl.hpp>

Collaboration diagram for dnnl::convolution_forward::desc:

Public Member Functions
	desc (prop_kind prop_kind, algorithm algorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
	Constructs a descriptor for a convolution forward propagation primitive with bias.
	desc (prop_kind prop_kind, algorithm algorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
	Constructs a descriptor for a convolution forward propagation primitive without bias.
	desc (prop_kind prop_kind, algorithm algorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
	Constructs a descriptor for a dilated convolution forward propagation primitive with bias.
	desc (prop_kind prop_kind, algorithm algorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
	Constructs a descriptor for a dilated convolution forward propagation primitive without bias.

Detailed Description

Descriptor for a convolution forward propagation primitive.

Examples

cnn_inference_f32.cpp, cnn_inference_int8.cpp, cnn_training_f32.cpp, convolution.cpp, cpu_cnn_training_bf16.cpp, and performance_profiling.cpp.

Constructor & Destructor Documentation

desc() [1/4]

dnnl::convolution_forward::desc::desc ( prop_kind prop_kind, algorithm algorithm, const memory::desc & src_desc, const memory::desc & weights_desc, const memory::desc & bias_desc, const memory::desc & dst_desc, const memory::dims & strides, const memory::dims & padding_l, const memory::dims & padding_r )

inline

Constructs a descriptor for a convolution forward propagation primitive with bias.

Inputs:

• src (dnnl::primitive_desc_base::src_desc(0))
• weights (dnnl::primitive_desc_base::weights_desc(0))
• bias (dnnl::primitive_desc_base::weights_desc(1))

Outputs:

• dst (dnnl::primitive_desc_base::dst_desc(0))

Note

All the memory descriptors may be initialized with the dnnl::memory::format_tag::any value of format_tag.

Parameters

prop_kind	Propagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithm	Convolution algorithm. Possible values are dnnl::algorithm::convolution_direct, dnnl::algorithm::convolution_winograd, and dnnl::algorithm::convolution_auto.
src_desc	Source memory descriptor.
weights_desc	Weights memory descriptor.
bias_desc	Bias memory descriptor. Passing zero memory descriptor disables the bias term.
dst_desc	Destination memory descriptor.
strides	Strides for each spatial dimension.
padding_l	Vector of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Vector of padding values for high indices for each spatial dimension (back, bottom, right).

desc() [2/4]

dnnl::convolution_forward::desc::desc ( prop_kind prop_kind, algorithm algorithm, const memory::desc & src_desc, const memory::desc & weights_desc, const memory::desc & dst_desc, const memory::dims & strides, const memory::dims & padding_l, const memory::dims & padding_r )

inline

Constructs a descriptor for a convolution forward propagation primitive without bias.

Inputs:

• src (dnnl::primitive_desc_base::src_desc(0))
• weights (dnnl::primitive_desc_base::weights_desc(0))

Outputs:

• dst (dnnl::primitive_desc_base::dst_desc(0))

Note

All the memory descriptors may be initialized with the dnnl::memory::format_tag::any value of format_tag.

Parameters

prop_kind	Propagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithm	Convolution algorithm. Possible values are dnnl::algorithm::convolution_direct, dnnl::algorithm::convolution_winograd, and dnnl::algorithm::convolution_auto.
src_desc	Source memory descriptor.
weights_desc	Weights memory descriptor.
dst_desc	Destination memory descriptor.
strides	Strides for each spatial dimension.
padding_l	Vector of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Vector of padding values for high indices for each spatial dimension (back, bottom, right).

desc() [3/4]

dnnl::convolution_forward::desc::desc ( prop_kind prop_kind, algorithm algorithm, const memory::desc & src_desc, const memory::desc & weights_desc, const memory::desc & bias_desc, const memory::desc & dst_desc, const memory::dims & strides, const memory::dims & dilates, const memory::dims & padding_l, const memory::dims & padding_r )

inline

Constructs a descriptor for a dilated convolution forward propagation primitive with bias.

Inputs:

• src (dnnl::primitive_desc_base::src_desc(0))
• weights (dnnl::primitive_desc_base::weights_desc(0))
• bias (dnnl::primitive_desc_base::weights_desc(1))

Outputs:

• dst (dnnl::primitive_desc_base::dst_desc(0))

Note

All the memory descriptors may be initialized with the dnnl::memory::format_tag::any value of format_tag.

Parameters

prop_kind	Propagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithm	Convolution algorithm. Possible values are dnnl::algorithm::convolution_direct, dnnl::algorithm::convolution_winograd, and dnnl::algorithm::convolution_auto.
src_desc	Source memory descriptor.
weights_desc	Weights memory descriptor.
bias_desc	Bias memory descriptor. Passing zero memory descriptor disables the bias term.
dst_desc	Destination memory descriptor.
strides	Strides for each spatial dimension.
dilates	Dilations for each spatial dimension. A zero value means no dilation in the corresponding dimension.
padding_l	Vector of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Vector of padding values for high indices for each spatial dimension (back, bottom, right).

desc() [4/4]

dnnl::convolution_forward::desc::desc ( prop_kind prop_kind, algorithm algorithm, const memory::desc & src_desc, const memory::desc & weights_desc, const memory::desc & dst_desc, const memory::dims & strides, const memory::dims & dilates, const memory::dims & padding_l, const memory::dims & padding_r )

inline

Constructs a descriptor for a dilated convolution forward propagation primitive without bias.

Inputs:

• src (dnnl::primitive_desc_base::src_desc(0))
• weights (dnnl::primitive_desc_base::weights_desc(0))

Outputs:

• dst (dnnl::primitive_desc_base::dst_desc(0))

Note

All the memory descriptors may be initialized with the dnnl::memory::format_tag::any value of format_tag.

Parameters

prop_kind	Propagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithm	Convolution algorithm. Possible values are dnnl::algorithm::convolution_direct, dnnl::algorithm::convolution_winograd, and dnnl::algorithm::convolution_auto.
src_desc	Source memory descriptor.
weights_desc	Weights memory descriptor.
dst_desc	Destination memory descriptor.
strides	Strides for each spatial dimension.
dilates	Dilations for each spatial dimension. A zero value means no dilation in the corresponding dimension.
padding_l	Vector of padding values for low indices for each spatial dimension (front, top, left).
padding_r	Vector of padding values for high indices for each spatial dimension (back, bottom, right).

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The documentation for this struct was generated from the following file:

• include/dnnl.hpp